Deteksi Lokasi Pencemaran Air Sungai Citarum berbasis IoT menggunakan Fuzzy Inference System

Authors

  • Annisa Gustien Widowati Telkom University
  • Novian Anggis Suwastika Telkom University
  • Rahmat Yasirandi Telkom University

DOI:

https://doi.org/10.34818/INDOJC.2019.4.3.315

Abstract

Citarum merupakan sumber dari denyut nadi perekonomian Indonesia sebesar 20% total produksi industri Indonesia dan sumber dari 60% produksi tekstil nasional. Kegiatan produksi tersebut menimbulkan permasalahan lingkungan akibat pembuangan limbah rumah tangga dan industri yang tidak menggunakan Instalasi Pengolahan Air Limbah (IPAL) secara optimal. Salah satu kendala dalam mengatasi pencemaran air sungai Citarum adalah menentukan lokasi dengan tingkat pencemaran tertinggi. Untuk mendeteksi lokasi pencemaran diperlukan pemantauan air sungai Citarum dengan pengambilan data terus-menerus secara realtime dan pengklasifikasian tingkat pencemaran dibutuhkan. Solusi dari permasalahan pendeteksian lokasi pencemaran dapat dibangun dengan memanfaatkan teknologi Internet of Things (IoT) sebagai solusi pembacaan data secara terus-menerus dan realtime. Kebutuhan klasifikasi didalam sistem diterapkan dengan metode fuzzy inference system tipe Mamdani dengan sifat dasar aturan yang dapat ditafsirkan, intuitif dan banyak digunakan khususnya untuk mendukung pengambilan keputusan yang dengan tingkat akurasi yang tinggi. Hasil yang didapatkan dari pengujian berdasarkan skenario pengujian tingkat akurasi klasifikasi sistem yang telah dilakukan menunjukkan akurasi sebesar 92% dengan nilai toleransi error pada sistem sebesar 4% serta toleransi akurasi pembacaan data oleh perangkat keras sistem yang dibangun menunjukkan pH 3.94%, TDS 4.92% dan suhu 1.84% dari deteksi di lima lokasi sungai Citarum di Bandung Selatan.

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Published

2020-01-07

How to Cite

Widowati, A. G., Suwastika, N. A., & Yasirandi, R. (2020). Deteksi Lokasi Pencemaran Air Sungai Citarum berbasis IoT menggunakan Fuzzy Inference System. Indonesian Journal on Computing (Indo-JC), 4(3), 1–14. https://doi.org/10.34818/INDOJC.2019.4.3.315

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Section

Computer Science

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